Audio response messages

ABSTRACT

An audio response system can generate multimodal messages that can be dynamically updated on viewer&#39;s client device based on a type of audio response detected. The audio responses can include keywords or continuum-based signal (e.g., levels of wind noise). A machine learning scheme can be trained to output classification data from the audio response data for content selection and dynamic display updates.

CLAIM OF PRIORITY

This application is a continuation of U.S. patent application Ser. No.16/418,638, filed on May 21, 2019, which claims the benefit of priorityto U.S. Provisional Patent Application Ser. No. 62/674,410, filed on May21, 2018, each of which are hereby incorporated by reference herein intheir entireties.

TECHNICAL FIELD

Embodiments of the present disclosure relate generally to virtualdisplay and, more particularly, but not by way of limitation, toaudio-based interactions with computational devices.

BACKGROUND

Some computers have limited computational resources. For example,smartphones generally have a relatively small screen size, limitedinput/output controls, and less memory and processor power than theirdesktop computer and laptop counterparts. Different issues arise wheninteracting with a computer with limited computational resources. Forexample, due to the limited input/out controls and small screen size,generating and interacting with dynamically updated content can bedifficult.

BRIEF DESCRIPTION OF THE DRAWINGS

To easily identify the discussion of any particular element or act, themost significant digit or digits in a reference number refer to thefigure (“FIG.”) number in which that element or act is first introduced.

FIG. 1 is a block diagram showing an example messaging system forexchanging data (e.g., messages and associated content) over a network.

FIG. 2 is block diagram illustrating further details regarding amessaging system having an integrated virtual object machine learningsystem, according to example embodiments.

FIG. 3 is a schematic diagram illustrating data which may be stored in adatabase of a messaging server system, according to certain exampleembodiments.

FIG. 4 is a schematic diagram illustrating a structure of a message,according to some embodiments, generated by a messaging clientapplication for communication.

FIG. 5 is a schematic diagram illustrating an example access-limitingprocess, in terms of which access to content (e.g., an ephemeral messageand associated multimedia payload of data) or a content collection(e.g., an ephemeral message story) may be time-limited (e.g., madeephemeral).

FIG. 6 shows internal functional components of an audio response system,according to some example embodiments.

FIG. 7A-7C show flow diagrams of methods for interacting with audioresponse ephemeral messages, according to some example embodiments.

FIG. 8A-8B show machine learning implementations for audio responseephemeral messages, according to some example embodiments.

FIG. 9 shows a finite state mechanism for content of an audio responsesystem, according to some example embodiments.

FIGS. 10-13 show user interfaces for audio response ephemeral messages,according to some example embodiments

FIG. 14 is a block diagram illustrating a representative softwarearchitecture, which may be used in conjunction with various hardwarearchitectures herein described.

FIG. 15 is a block diagram illustrating components of a machine,according to some example embodiments, able to read instructions from amachine-readable medium (e.g., a machine-readable storage medium) andperform any one or more of the methodologies discussed herein.

DETAILED DESCRIPTION

The description that follows includes systems, methods, techniques,instruction sequences, and computing machine program products thatembody illustrative embodiments of the disclosure. In the followingdescription, for the purposes of explanation, numerous specific detailsare set forth in order to provide an understanding of variousembodiments of the inventive subject matter. It will be evident,however, to those skilled in the art, that embodiments of the inventivesubject matter may be practiced without these specific details. Ingeneral, well-known instruction instances, protocols, structures, andtechniques are not necessarily shown in detail.

An audio response system can generate audio response messages thatmonitor audio data to determine if the viewing user is interacting withthe audio response system on a user device (e.g., smartphone). The audioresponse system can include notifications, such as text instructions,graphics, icons, that indicate to the viewing user what type of audiointeraction to perform. For example, the audio response system canprompt the user to whistle loudly or whistle a certain note, or verballyspeak a described keyword, and so on. In some example embodiments, whattype of audio data will trigger a display of content on the audioresponse message is selected by the sending user. For example, a sendinguser that creates an audio response message can specify that the viewinguser should utter or speak a keyword or whistle to unlock data on theviewing device.

The audio response system can record sound data in an audio waveformformat, convert the audio waveform formatted data into visual sound data(e.g., spectrogram), and classify the visual sound data using aconvolutional neural network to determine whether the recorded dataincludes a pre-specified type of audio interaction. If thepre-configured audio interaction is detected, additional actions can beperformed, such as music being played on the viewing user's device oroverlay content being display on the viewing user's device.

FIG. 1 is a block diagram showing an example messaging system 100 forexchanging data (e.g., messages and associated content) over a network.The messaging system 100 includes multiple client devices 102, each ofwhich hosts a number of applications including a messaging clientapplication 104. Each messaging client application 104 iscommunicatively coupled to other instances of the messaging clientapplication 104 and a messaging server system 108 via a network 106(e.g., the Internet).

Accordingly, each messaging client application 104 is able tocommunicate and exchange data with another messaging client application104 and with the messaging server system 108 via the network 106. Thedata exchanged between messaging client applications 104, and between amessaging client application 104 and the messaging server system 108,includes functions (e.g., commands to invoke functions) as well aspayload data (e.g., text, audio, video, or other multimedia data).

The messaging server system 108 provides server-side functionality viathe network 106 to a particular messaging client application 104. Whilecertain functions of the messaging system 100 are described herein asbeing performed by either a messaging client application 104 or by themessaging server system 108, it will be appreciated that the location ofcertain functionality within either the messaging client application 104or the messaging server system 108 is a design choice. For example, itmay be technically preferable to initially deploy certain technology andfunctionality within the messaging server system 108, but to latermigrate this technology and functionality to the messaging clientapplication 104 where a client device 102 has a sufficient processingcapacity.

The messaging server system 108 supports various services and operationsthat are provided to the messaging client application 104. Suchoperations include transmitting data to, receiving data from, andprocessing data generated by the messaging client application 104. Thisdata may include message content, client device information, geolocationinformation, media annotation and overlays, message content persistenceconditions, social network information, and live event information, asexamples. Data exchanges within the messaging system 100 are invoked andcontrolled through functions available via user interfaces (UIs) of themessaging client application 104.

Turning now specifically to the messaging server system 108, anApplication Programming Interface (API) server 110 is coupled to, andprovides a programmatic interface to, an application server 112. Theapplication server 112 is communicatively coupled to a database server118, which facilitates access to a database 120 in which is stored dataassociated with messages processed by the application server 112.

The API server 110 receives and transmits message data (e.g., commandsand message payloads) between the client devices 102 and the applicationserver 112. Specifically, the API server 110 provides a set ofinterfaces (e.g., routines and protocols) that can be called or queriedby the messaging client application 104 in order to invoke functionalityof the application server 112. The API server 110 exposes variousfunctions supported by the application server 112, including accountregistration; login functionality; the sending of messages, via theapplication server 112, from a particular messaging client application104 to another messaging client application 104; the sending of mediafiles (e.g., images or video) from a messaging client application 104 toa messaging server application 114 for possible access by anothermessaging client application 104; the setting of a collection of mediadata (e.g., a story); the retrieval of such collections; the retrievalof a list of friends of a user of a client device 102; the retrieval ofmessages and content; the adding and deletion of friends to and from asocial graph; the location of friends within the social graph; andopening application events (e.g., relating to the messaging clientapplication 104).

The application server 112 hosts a number of applications andsubsystems, including the messaging server application 114, an imageprocessing system 116, and a social network system 122. The messagingserver application 114 implements a number of message-processingtechnologies and functions, particularly related to the aggregation andother processing of content (e.g., textual and multimedia content)included in messages received from multiple instances of the messagingclient application 104. As will be described in further detail, the textand media content from multiple sources may be aggregated intocollections of content (e.g., called stories or galleries). Thesecollections are then made available, by the messaging server application114, to the messaging client application 104. Other processor- andmemory-intensive processing of data may also be performed server-side bythe messaging server application 114, in view of the hardwarerequirements for such processing.

The application server 112 also includes the image processing system116, which is dedicated to performing various image processingoperations, typically with respect to images or video received withinthe payload of a message at the messaging server application 114.

The social network system 122 supports various social networkingfunctions and services and makes these functions and services availableto the messaging server application 114. To this end, the social networksystem 122 maintains and accesses an entity graph (e.g., entity graph304 in FIG. 3) within the database 120. Examples of functions andservices supported by the social network system 122 include theidentification of other users of the messaging system 100 with whom aparticular user has relationships or whom the particular user is“following,” and also the identification of other entities and interestsof a particular user.

The application server 112 is communicatively coupled to a databaseserver 118, which facilitates access to a database 120 in which isstored data associated with messages processed by the messaging serverapplication 114.

FIG. 2 is block diagram illustrating further details regarding themessaging system 100, according to example embodiments. Specifically,the messaging system 100 is shown to comprise the messaging clientapplication 104 and the application server 112, which in turn embody anumber of subsystems, namely an ephemeral timer system 202, a collectionmanagement system 204, an annotation system 206, and an audio responsesystem 250.

The ephemeral timer system 202 is responsible for enforcing thetemporary access to content permitted by the messaging clientapplication 104 and the messaging server application 114. To this end,the ephemeral timer system 202 incorporates a number of timers that,based on duration and display parameters associated with a message orcollection of messages (e.g., a sequential ephemeral message story),selectively display and enable access to messages and associated contentvia the messaging client application 104. Further details regarding theoperation of the ephemeral timer system 202 are provided below.

The collection management system 204 is responsible for managingcollections of media (e.g., collections of text, image, video, and audiodata). In some examples, a collection of content (e.g., messages,including images, video, text, and audio) may be organized into an“event gallery” or an “event story.” Such a collection may be madeavailable for a specified time period, such as the duration of an eventto which the content relates. For example, content relating to a musicconcert may be made available as a “story” for the duration of thatmusic concert. The collection management system 204 may also beresponsible for publishing an icon that provides notification of theexistence of a particular collection to the user interface of themessaging client application 104.

The collection management system 204 furthermore includes a curationinterface 208 that allows a collection manager to manage and curate aparticular collection of content. For example, the curation interface208 enables an event organizer to curate a collection of contentrelating to a specific event (e.g., delete inappropriate content orredundant messages). Additionally, the collection management system 204employs machine vision (or image recognition technology) and contentrules to automatically curate a content collection. In certainembodiments, compensation may be paid to a user for inclusion ofuser-generated content into a collection. In such cases, the curationinterface 208 operates to automatically make payments to such users forthe use of their content.

The annotation system 206 provides various functions that enable a userto annotate or otherwise modify or edit media content associated with amessage. For example, the annotation system 206 provides functionsrelated to the generation and publishing of media overlays for messagesprocessed by the messaging system 100. The annotation system 206operatively supplies a media overlay (e.g., geofilter or filter) to themessaging client application 104 based on a geolocation of the clientdevice 102. In another example, the annotation system 206 operativelysupplies a media overlay to the messaging client application 104 basedon other information, such as social network information of the user ofthe client device 102. A media overlay may include audio and visualcontent and visual effects. Examples of audio and visual content includepictures, texts, logos, animations, and sound effects. An example of avisual effect includes color overlaying. The audio and visual content orthe visual effects can be applied to a media content item (e.g., aphoto) at the client device 102. For example, the media overlay includestext that can be overlaid on top of a photograph generated by the clientdevice 102. In another example, the media overlay includes anidentification of a location (e.g., Venice Beach), a name of a liveevent, or a name of a merchant (e.g., Beach Coffee House). In anotherexample, the annotation system 206 uses the geolocation of the clientdevice 102 to identify a media overlay that includes the name of amerchant at the geolocation of the client device 102. The media overlaymay include other indicia associated with the merchant. The mediaoverlays may be stored in the database 120 and accessed through thedatabase server 118.

In one example embodiment, the annotation system 206 provides auser-based publication platform that enables users to select ageolocation on a map and upload content associated with the selectedgeolocation. The user may also specify circumstances under whichparticular content should be offered to other users. The annotationsystem 206 generates a media overlay that includes the uploaded contentand associates the uploaded content with the selected geolocation.

In another example embodiment, the annotation system 206 provides amerchant-based publication platform that enables merchants to select aparticular media overlay associated with a geolocation via a biddingprocess. For example, the annotation system 206 associates the mediaoverlay of a highest-bidding merchant with a corresponding geolocationfor a predefined amount of time.

The audio response system 250 manages interactions with audio responseephemeral messages, as discussed in further detail below.

FIG. 3 is a schematic diagram illustrating data 300 which may be storedin the database 120 of the messaging server system 108, according tocertain example embodiments. While the content of the database 120 isshown to comprise a number of tables, it will be appreciated that thedata could be stored in other types of data structures (e.g., as anobject-oriented database).

The database 120 includes message data stored within a message table314. An entity table 302 stores entity data, including an entity graph304. Entities for which records are maintained within the entity table302 may include individuals, corporate entities, organizations, objects,places, events, and so forth. Regardless of type, any entity regardingwhich the messaging server system 108 stores data may be a recognizedentity. Each entity is provided with a unique identifier, as well as anentity type identifier (not shown).

The entity graph 304 furthermore stores information regardingrelationships and associations between or among entities. Suchrelationships may be social, professional (e.g., work at a commoncorporation or organization), interested-based, or activity-based,merely for example.

The database 120 also stores annotation data, in the example form offilters, in an annotation table 312. Filters for which data is storedwithin the annotation table 312 are associated with and applied tovideos (for which data is stored in a video table 310) and/or images(for which data is stored in an image table 308). Filters, in oneexample, are overlays that are displayed as overlaid on an image orvideo during presentation to a recipient user. Filters may be of varioustypes, including user-selected filters from a gallery of filterspresented to a sending user by the messaging client application 104 whenthe sending user is composing a message. Other types of filters includegeolocation filters (also known as geo-filters) which may be presentedto a sending user based on geographic location. For example, geolocationfilters specific to a neighborhood or special location may be presentedwithin a user interface by the messaging client application 104, basedon geolocation information determined by a Global Positioning System(GPS) unit of the client device 102. Another type of filter is a datafilter, which may be selectively presented to a sending user by themessaging client application 104, based on other inputs or informationgathered by the client device 102 during the message creation process.Examples of data filters include a current temperature at a specificlocation, a current speed at which a sending user is traveling, abattery life for a client device 102, or the current time.

Other annotation data that may be stored within the image table 308 isso-called “lens” data. A “lens” may be a real-time special effect andsound that may be added to an image or a video. In some exampleembodiments, the lens is stored as lens metadata which is retrievable ascontent (e.g., cartoon cake 1100 discussed below), discussed in furtherdetail below.

As mentioned above, the video table 310 stores video data which, in oneembodiment, is associated with messages for which records are maintainedwithin the message table 314. Similarly, the image table 308 storesimage data associated with messages for which message data is stored inthe message table 314. The entity table 302 may associate variousannotations from the annotation table 312 with various images and videosstored in the image table 308 and the video table 310.

A story table 306 stores data regarding collections of messages andassociated image, video, or audio data, which are compiled into acollection (e.g., a story or a gallery). The creation of a particularcollection may be initiated by a particular user (e.g., each user forwhom a record is maintained in the entity table 302). A user may createa “personal story” in the form of a collection of content that has beencreated and sent/broadcast by that user. To this end, the user interfaceof the messaging client application 104 may include an icon that isuser-selectable to enable a sending user to add specific content to hisor her personal story.

A collection may also constitute a “live story,” which is a collectionof content from multiple users that is created manually, automatically,or using a combination of manual and automatic techniques. For example,a “live story” may constitute a curated stream of user-submitted contentfrom various locations and events. Users whose client devices havelocation services enabled and are at a common location or event at aparticular time may, for example, be presented with an option, via auser interface of the messaging client application 104, to contributecontent to a particular live story. The live story may be identified tothe user by the messaging client application 104, based on his or herlocation. The end result is a “live story” told from a communityperspective.

A further type of content collection is known as a “location story,”which enables a user whose client device 102 is located within aspecific geographic location (e.g., on a college or university campus)to contribute to a particular collection. In some embodiments, acontribution to a location story may require a second degree ofauthentication to verify that the end user belongs to a specificorganization or other entity (e.g., is a student on the universitycampus).

FIG. 4 is a schematic diagram illustrating a structure of a message 400,according to some embodiments, generated by a messaging clientapplication 104 for communication to a further messaging clientapplication 104 or the messaging server application 114. The content ofa particular message 400 is used to populate the message table 314stored within the database 120, accessible by the messaging serverapplication 114. Similarly, the content of a message 400 is stored inmemory as “in-transit” or “in-flight” data of the client device 102 orthe application server 112. The message 400 is shown to include thefollowing components:

-   -   A message identifier 402: a unique identifier that identifies        the message 400.    -   A message text payload 404: text to be generated by a user via a        user interface of the client device 102 and that is included in        the message 400.    -   A message image payload 406: image data captured by a camera        component of a client device 102 or retrieved from memory of a        client device 102 and included in the message 400.    -   A message video payload 408: video data captured by a camera        component or retrieved from a memory component of the client        device 102 and included in the message 400.    -   A message audio payload 410: audio data captured by a microphone        or retrieved from the memory component of the client device 102        and included in the message 400.    -   Message annotations 412: annotation data (e.g., filters,        stickers, or other enhancements) that represents annotations to        be applied to the message image payload 406, message video        payload 408, or message audio payload 410 of the message 400.    -   A message duration parameter 414: a parameter value indicating,        in seconds, the amount of time for which content of the message        400 (e.g., the message image payload 406, message video payload        408, and message audio payload 410) is to be presented or made        accessible to a user via the messaging client application 104.    -   A message geolocation parameter 416: geolocation data (e.g.,        latitudinal and longitudinal coordinates) associated with the        content payload of the message 400. Multiple message geolocation        parameter 416 values may be included in the payload, with each        of these parameter values being associated with respective        content items included in the content (e.g., a specific image in        the message image payload 406, or a specific video in the        message video payload 408).    -   A message story identifier 418: identifier values identifying        one or more content collections (e.g., “stories”) with which a        particular content item in the message image payload 406 of the        message 400 is associated. For example, multiple images within        the message image payload 406 may each be associated with        multiple content collections using identifier values.    -   A message tag 420: one or more tags, each of which is indicative        of the subject matter of content included in the message        payload. For example, where a particular image included in the        message image payload 406 depicts an animal (e.g., a lion), a        tag value may be included within the message tag 420 that is        indicative of the relevant animal. Tag values may be generated        manually, based on user input, or may be automatically generated        using, for example, image recognition.    -   A message sender identifier 422: an identifier (e.g., a        messaging system identifier, email address, or device        identifier) indicative of a user of the client device 102 on        which the message 400 was generated and from which the message        400 was sent.    -   A message receiver identifier 424: an identifier (e.g., a        messaging system identifier, email address, or device        identifier) indicative of a user of the client device 102 to        which the message 400 is addressed.

The contents (e.g., values) of the various components of the message 400may be pointers to locations in tables within which content data valuesare stored. For example, an image value in the message image payload 406may be a pointer to (or address of) a location within the image table308. Similarly, values within the message video payload 408 may point todata stored within the video table 310, values stored within the messageannotations 412 may point to data stored in the annotation table 312,values stored within the message story identifier 418 may point to datastored in the story table 306, and values stored within the messagesender identifier 422 and the message receiver identifier 424 may pointto user records stored within the entity table 302.

FIG. 5 is a schematic diagram illustrating an access-limiting process500, in terms of which access to content (e.g., an ephemeral message502, and associated multimedia payload of data) or a content collection(e.g., an ephemeral message story 504), may be time-limited (e.g., madeephemeral).

An ephemeral message 502 is shown to be associated with a messageduration parameter 506, the value of which determines an amount of timethat the ephemeral message 502 will be displayed to a receiving user ofthe ephemeral message 502 by the messaging client application 104. Inone embodiment, where the messaging client application 104 is anapplication client, an ephemeral message 502 is viewable by a receivinguser for up to a maximum of 10 seconds, depending on the amount of timethat the sending user specifies using the message duration parameter506.

The message duration parameter 506 and the message receiver identifier424 are shown to be inputs to a message timer 512, which is responsiblefor determining the amount of time that the ephemeral message 502 isshown to a particular receiving user identified by the message receiveridentifier 424. In particular, the ephemeral message 502 will only beshown to the relevant receiving user for a time period determined by thevalue of the message duration parameter 506. The message timer 512 isshown to provide output to a more generalized ephemeral timer system202, which is responsible for the overall timing of display of content(e.g., an ephemeral message 502) to a receiving user.

The ephemeral message 502 is shown in FIG. 5 to be included within anephemeral message story 504 (e.g., a personal story, or an event story).The ephemeral message story 504 has an associated story durationparameter 508, a value of which determines a time duration for which theephemeral message story 504 is presented and accessible to users of themessaging system 100. The story duration parameter 508, for example, maybe the duration of a music concert, where the ephemeral message story504 is a collection of content pertaining to that concert.Alternatively, a user (either the owning user or a curator user) mayspecify the value for the story duration parameter 508 when performingthe setup and creation of the ephemeral message story 504.

Additionally, each ephemeral message 502 within the ephemeral messagestory 504 has an associated story participation parameter 510, a valueof which determines the duration of time for which the ephemeral message502 will be accessible within the context of the ephemeral message story504. Accordingly, a particular ephemeral message 502 may “expire” andbecome inaccessible within the context of the ephemeral message story504, prior to the ephemeral message story 504 itself expiring in termsof the story duration parameter 508. The story duration parameter 508,story participation parameter 510, and message receiver identifier 424each provide input to a story timer 514, which operationally determineswhether a particular ephemeral message 502 of the ephemeral messagestory 504 will be displayed to a particular receiving user and, if so,for how long. Note that the ephemeral message story 504 is also aware ofthe identity of the particular receiving user as a result of the messagereceiver identifier 424.

Accordingly, the story timer 514 operationally controls the overalllifespan of an associated ephemeral message story 504, as well as anindividual ephemeral message 502 included in the ephemeral message story504. In one embodiment, each and every ephemeral message 502 within theephemeral message story 504 remains viewable and accessible for a timeperiod specified by the story duration parameter 508. In a furtherembodiment, a certain ephemeral message 502 may expire, within thecontext of the ephemeral message story 504, based on a storyparticipation parameter 510. Note that a message duration parameter 506may still determine the duration of time for which a particularephemeral message 502 is displayed to a receiving user, even within thecontext of the ephemeral message story 504. Accordingly, the messageduration parameter 506 determines the duration of time that a particularephemeral message 502 is displayed to a receiving user, regardless ofwhether the receiving user is viewing that ephemeral message 502 insideor outside the context of an ephemeral message story 504.

The ephemeral timer system 202 may furthermore operationally remove aparticular ephemeral message 502 from the ephemeral message story 504based on a determination that it has exceeded an associated storyparticipation parameter 510. For example, when a sending user hasestablished a story participation parameter 510 of 24 hours fromposting, the ephemeral timer system 202 will remove the relevantephemeral message 502 from the ephemeral message story 504 after thespecified 24 hours. The ephemeral timer system 202 also operates toremove an ephemeral message story 504 either when the storyparticipation parameter 510 for each and every ephemeral message 502within the ephemeral message story 504 has expired, or when theephemeral message story 504 itself has expired in terms of the storyduration parameter 508.

In certain use cases, a creator of a particular ephemeral message story504 may specify an indefinite story duration parameter 508. In thiscase, the expiration of the story participation parameter 510 for thelast remaining ephemeral message 502 within the ephemeral message story504 will determine when the ephemeral message story 504 itself expires.In this case, a new ephemeral message 502, added to the ephemeralmessage story 504, with a new story participation parameter 510,effectively extends the life of an ephemeral message story 504 to equalthe value of the story participation parameter 510.

In response to the ephemeral timer system 202 determining that anephemeral message story 504 has expired (e.g., is no longer accessible),the ephemeral timer system 202 communicates with the messaging system100 (e.g., specifically, the messaging client application 104) to causean indicium (e.g., an icon) associated with the relevant ephemeralmessage story 504 to no longer be displayed within a user interface ofthe messaging client application 104. Similarly, when the ephemeraltimer system 202 determines that the message duration parameter 506 fora particular ephemeral message 502 has expired, the ephemeral timersystem 202 causes the messaging client application 104 to no longerdisplay an indicium (e.g., an icon or textual identification) associatedwith the ephemeral message 502.

FIG. 6 shows internal functional engines of an audio response system250, according to some example embodiments. As illustrated, the audioresponse system 250 comprises an interface engine 605, a detectionengine 610, and a response engine 615. The interface engine 605 managesgenerating audio response ephemeral message data for transmission anddisplay on another client device. For example, the interface engine 605can present a user of a client device one or more options for a type ofaudio responsive message to generate and transmit to another clientdevice for display. The detection engine 610 manages detecting audioresponses from a recipient user viewing the audio response ephemeralmessage on their client device. For example, the detection engine 610can implement a machine learning scheme (e.g., a convolutional neuralnetwork) to detect a type of audio response created by (e.g., utteredby, emanating from) a recipient user that is viewing the audio responsemessage. The response engine 615 manages selection and display ofcontent in response to the type of audio response detected by thedetection engine 610. For example, in response to the detection engine610 detecting a preselected keyword, the response engine 615 displaysone or more items of content as part of an ephemeral message for displayon the recipient's client device, and/or publication to a social networksite. As an additional example, in response to the detection engine 610detecting sound noise from the user blowing air, the response engine 615displays a cartoon cake with candles flickering on the user's clientdevice.

FIG. 7A-7C show flow diagrams of methods for interacting with audioresponse ephemeral messages, according to some example embodiments. Inthe illustrated example, method 700 of FIG. 7A is performed by a sendinguser via his/her client device (an instance of system 250 executing onthe sending user's device) to generate the audio response message forinteraction, and methods 725 and 750 (of FIG. 7B, 7C respectively) areperformed by a recipient user via his/her client device (anotherinstance of system 250 on the sending user's device) to interact withthe audio response message using audio interactions (e.g., blowing onthe phone, snapping fingers, whistling, speaking keywords).

With reference to method 700 of FIG. 7A, at operation 705, the interfaceengine 605 receives message data from the first client device forconstruction of an audio response ephemeral message. For example, atoperation 705 the interface engine 605 may use an image capture sensor(e.g., a CCD sensor, a CMOS sensor) and a transducer (e.g., amicrophone) to record video data of a first user singing a song, such as“Happy Birthday”.

At operation 710, the interface engine 605 determines content to includein an audio response message. In some example embodiments, the userselects the audio response message type as a birthday message type usinga user interface button displayed on the display screen of the clientdevice. In some example embodiments, the interface engine 605 isconfigured to detect which type of message should be displayed based onwhat the first user is recording. For example, the interface engine 605may use a machine learning scheme (e.g., recursive neural networktrained using word embeddings) to detect that the happy birthday melodyis being sung, and responsive to the detection, generate a birthday typeaudio response message with associated content for display (e.g., abirthday cake with candles that animate upon detection of wind noise).

At operation 715, the interface engine 605 generates an audio responseephemeral message comprising the generated image content (e.g., videodata of the user singing and content data including the cake animationcontent or a reference to a local or remote storage location of the cakeanimation content). At operation 720, the interface engine 605 transmitsthe audio response ephemeral message (e.g., transmission to another userdevice of a recipient user, or publishes the audio response ephemeralmessage to a social network site for access by other users).

With reference to method 725 in FIG. 7B, at operation 730, the interfaceengine 605 (executing in another instance of system 250 on therecipient's user device) receives the audio response ephemeral message.At operation 735, the interface engine 605 displays the audio responseephemeral message. The display of the audio response ephemeral messagemay include the video of the sending user singing and one or moreindications to perform an audio interaction with the recipient user'sclient device. For example, the audio response ephemeral message cancontain text the prompts the recipient user to blow air towards thescreen displaying the audio response ephemeral message.

At operation 740, the detection engine 610 identifies audio data createdin response to viewing the audio responsive ephemeral message.Continuing the example, the audio response ephemeral message includes aninstruction to prompt the recipient user to blow air onto the clientdevice in an attempt to extinguish cartoon candles being displayed aspart of the audio responsive ephemeral message. In some exampleembodiments, upon the audio response ephemeral message being activated(e.g., displayed), the detection engine 610 implements a convolutionalneural network to analyze sound data generated by the viewing device anddetermine whether the sound data includes wind sounds (e.g., wind noisegenerated by the user blowing air past the microphone of the userdevice). At operation 745, in response to sound data including apre-configured type (e.g., wind sounds), the response engine 615corresponding content, such as a cake animation with candles flickeringin response to virtual wind currents.

FIG. 7C shows an example method 750 for detecting audio response data,according to some example embodiments. In the example of method 750, thedetection engine 610 is configured to identify non-verbal sounds (e.g.,wind noise, whistling, popping noises) at different intensities, andfurther configured to generate a success or completion value if apre-configured non-verbal sound is detected at a pre-configuredintensity. In some example embodiments, the method 750 is implemented asa sub-routine of operation 740 in FIG. 7B, in which audio response datais identified.

At operation 755, in response to the audio response ephemeral messagebeing displayed on the recipient's user device, the detection engine 610generates sound data. For example, the detection engine 610 initiates atransducer (e.g., microphone) of the user device to record soundwaveform data (e.g., .wav format files, .mp3 format files) of theambient or surrounding environment of the recipient user's device. Atoperation 760, the detection engine 610 identifies the stored soundwaveform data and converts the sound waveform data into visual sounddata, such as a spectrogram.

At operation 765, the detection engine 610 determines whether therecorded sound data is non-verbal data (e.g., wind, whistling) or verbaldata (e.g., spoken words). Upon determining that the sound data includesverbal data, the method 750 continues to operation 767 in which keywordsare identified, and the method 750 loops to operation 755 for furtherprocessing, according to some example embodiments. In some exampleembodiments, keywords do not initiate further processes and operation767 is omitted. For example, if at operation 765 the detection engine610 determines that the sound data does not contain the pre-configurednon-verbal sound, the method 750 proceeds directly to operation 755 forfurther monitoring (skipping operation 767 in FIG. 7C).

In contrast, if at operation 765 the detection engine 610 determinesthat the visual sound data contains non-verbal sound data, then then atoperation 770 the detection engine 610 further determines whether thenon-verbal data satisfies a pre-configured intensity level. For example,if at operation 765 the detection engine 610 determines that the visualsound data contains wind noise, then at operation 770 the detectionengine 610 determines whether the wind noise is loud wind noise (e.g.,high amplitude sound data of wind noise). If the non-verbal data doesnot satisfy the intensity threshold, then at operation 775 the detectionengine 610 causes display of a notification to prompt the user toincrease the intensity of the audio interaction (e.g., a popup windowcontaining the text “blow harder!”). After operation 775, the method 750continues to operation 755 for further monitoring. Alternatively, if thedetection engine 610 at operation 770 determines that the intensitylevel is satisfied (e.g., the wind noise is sufficiently loud orintense), then at operation 777 the detection engine stores a completionvalue to indicate that the pre-configured non-verbal sound of apre-configured intensity was detected. In some example embodiments,after operation 777, the subroutine terminates and the response engine615 identifies the completion value of operation 777 or keywords ofoperation 767 and displays corresponding content associated with thedetected data.

FIG. 8A shows an example configuration of detection engine 610,according to some example embodiments. In some example embodiments, thedetection engine 610 comprises two models: a sound convolutional neuralnetwork model 810 and a speech convolutional neural network model 815.The sound convolutional neural network model 810 is trained on Melspectrogram data to detect ambient environment sounds or non-verbalsounds.

FIG. 8B shows an example of mel spectrogram data for training anddetection. Generally, spectrogram data is a visual image of frequency ofthe sound plotted vertically over time plotted horizontally, and a melspectrogram is spectrogram mapped to the mel scale spectrum for humanauditory based sounds. Mel spectrogram 850 is visual sound data from arecording of wind blowing past a microphone at low intensity, and melspectrogram 855 is visual sound data from a recording of wind blowingpast a microphone at high intensity.

In some example embodiments, the sound convolutional neural networkmodel 810 is an image classification neural network trained to detectnon-verbal sounds, where the training data includes images of thenon-verbal sounds to be detected in mel spectrogram format (e.g., melspectrograms of low intensity wind, medium intensity wind, highintensity wind, loud slapping sound, soft clapping sound, high pitchednote of a human whistling, low pitched node of a human whistling, and soon.). In some example embodiments, the sound convolutional neuralnetwork 810 is trained only on images of wind noise intensityspectrograms and the detection engine 810 only generates likelihoodsthat recorded sound (e.g., recorded while the audio response ephemeralmessage is displayed) is of a wind noise type. For example, the trainingdata can comprise visual sound spectrograms of non-verbal sounds at 10different intensities, and the sound convolutional neural network 810processes any input data (e.g., a spectrogram comprising verbal data, aspectrogram comprising whistle data, a spectrogram comprising wind noisefrom wind currents from the weather, etc.) and generates numericallikelihoods that the input data falls into the trained intensitycategories for that type of sound. Further, although verbal andnon-verbal are discussed here as examples, it is appreciated thatnon-verbal is only an example and the intensity training approaches canapplied to spoken word data as well, according to some exampleembodiments. For example, the sound convolutional neural network can betrained to determine whether the viewing user is whispering the word“apple” or yelling the word “apple”.

In some example embodiments, the mel spectrogram data is furtherprocessed to generate mel-frequency cepstral coefficients (MFCC) data byapplying discrete cosine transfer (DCT) to mel spectrum data. In someexample embodiments, the speech convolutional neural network model 815is an image classification convolutional neural network trained togenerate keyword classification data 825, where the training dataincludes images of the keywords to be detected in MFCC format.

In the illustrated example of FIG. 8A, a user 800 generates a sound 803(e.g., a spoken word, a whistle, wind noise). The sound 803 is recordedby a microphone and converted into visual sound data 805 (e.g., aspectrogram). In some example embodiments, the visual sound data 805 isthen input into the sound convolutional neural network model 810 togenerate classification data 820 describing whether the visual sounddata is of a specified non-verbal sound, what intensity, and so on. Insome example embodiments, the sound convolutional neural network model810 is trained on a plurality of non-verbal sounds (e.g., individualspectrogram files of a non-verbal sound type at different intensities),and the classification data 820 is a ranking of likelihoods that thevisual sound data 805 falls into each of the trained non-verbal sounds(e.g., high wind noise=90% similarity score, low wind noise 10%similarity score, and so on).

In some example embodiments, the visual sound data 805 (e.g., afterbeing further processed by converting mel spectrogram data into MFCCdata) is input into the speech convolutional neural network model 815 togenerate a classification indicating keywords in the sound data.

In some example embodiments, the audio response ephemeral messageidentifies which model (e.g., the sound convolutional neural networkmodel 810 or the speech convolutional neural network model 815) toimplement to detect the sending user's selections. For example, theaudio response message is a birthday type (with wind responsiveelements), then sound convolutional neural network model 810 isimplemented, whereas if the audio response message is of a keyword type(e.g., a keyword guessing game), then a speech convolutional neuralnetwork model 815 is implemented.

FIG. 9 shows an example finite state machine of the audio responsesystem 250, according to some example embodiments. In some exampleembodiments, each sound intensity type can trigger different content fordisplay. For example, if a user blows medium intensity wind, one type ofcontent is triggered (e.g., unlocked, displayed), whereas if the userblows high intensity wind, a different type of content is triggered. Thefinite state machine (FSM) 900 tracks content in multi-intensity soundimplementations. The FSM 900 comprises an inactive state 905, an initialstate 920, an intermediate state 935, and a final state 950. In theinactive state 905, the detection engine 610 does not record audio dataand the response engine 615 does not display content.

Upon the generated audio response ephemeral message being published,transmitted, or opened for viewing on a client device (e.g., displayedon a recipient's device, the audio response system 250 transitions 915to the initial state 920. In the initial state 920, the detection engine610 is activated to classify audio data generated by the recipient userand displays default content associated with the initial state (e.g.,five candles lit on a birthday cake). In some example embodiments, solong as the response engine 615 is not triggered by preselected keywordsor thresholds (e.g., level of noise intensity), the audio responsesystem 250 remains in the initial state 920, as indicated by loop 925.

In response to the response engine 615 detecting audio trigger data ofthe intermediate state 935, the audio response system 250 transitions930 to the intermediate state 935. In the intermediate state 935, theresponse engine 615 displays new content on the display device as partof the audio response ephemeral message. For example, if in the initialstate 920, the user blows air of medium intensity towards the directionof the client device, the audio response system 250 in the intermediatestate 935 animates a portion but not all of the candles as beingextinguished (e.g., extinguishes all but two candles). So long as theuser does not perform any further actions, the audio response system 250remains in the intermediate state 935 as indicated by loop 940,according to some example embodiments.

If the user performs additional actions (e.g., blowing harder into amicrophone of the client device) the audio response system 250transitions 945 to the final state 950 where the response engine 615displays new content pre-associated with the final state 950. Forexample, in the final state 950, the response engine 615 displays abirthday cake as having all of its candles extinguished.

As indicated by transition 955, in some example embodiments, theresponse engine 615 transitions directly from the initial state 920 tothe final state 950. For example, a user that is viewing a birthday cakewith all candles alight, may blow very hard thereby causing the audioresponse system 250 to transition 955 to the final state 950 in whichthe birthday cake is displayed with all candles having beenextinguished, thereby skipping the intermediate state and contentassociated with the intermediate state 935.

FIGS. 10-13 show example user interfaces for generation and display ofaudio response ephemeral messages, according to some exampleembodiments. FIG. 10 shows an example client device 1000 of a first user(e.g., “Alice”, a sending user) while the first user generates the audioresponse ephemeral message. As illustrated, the client device 1000includes an interactive touchscreen display 1010 that the first user canuse to generate an audio response ephemeral message. For example, thefirst user may select the user interface button 1007 to display acartoon avatar image of the first user 1015 interacting with a cartoonavatar image of the second user 1020 in a celebratory context.

As an additional example, the first user can select button 1006 tocreate a keyword type audio response ephemeral message. For instance,the first user can select a keyword “DOG” then record a video via camera1009 to include in the message of the first user describing or actingout dog like traits (to provide hints of the secret keyword to guess).The viewing user's device then monitors audio data and determineswhether the viewing user guess the secret keyword correctly via analysisof visual audio data spoken by the viewing user (e.g., MFCC data of theviewing user saying “dog”). In some embodiments, the sending user canselect a non-verbal audio trigger for the message. For example, the usercan specify via UI buttons whether the cake candles should extinguish inresponse to high intensity wind, low intensity wind, whistling sounds, asnapping sound, and so on, to more finely customize how a viewing userwill interact with the audio response ephemeral message.

FIG. 11 shows a client device 1101 of a second user (e.g., “Bob”)displaying the generated audio response ephemeral message 1102,according to some example embodiments. audio response ephemeral message1102 includes an instruction 1105 that prompts the second user tointeract with content of the audio response ephemeral message 1102. Forexample, the instruction 1105 prompts the user to blow towards a cartooncake 1100 to extinguish the cartoon candles on the cake. When the seconduser blows towards the client device 1101, a bottom side microphone 1107records audio data for input and classification by the detection engine610 as discussed above.

FIG. 12 shows example interactions of an audio response ephemeralmessage 1102, according to some example embodiments. In response to thesecond user not blowing hard enough, the updated cartoon cake 1200 isdisplayed in which some but not all the candles are animated asextinguished. Further in response to the interaction, a new instruction1205 may prompt the viewing user to blow harder on the cartoon cake 1200and attempt to extinguish the remaining candles.

FIG. 13 shows example interactions of an audio response ephemeralmessage 1102, according to some example embodiments. In the example ofFIG. 13, the viewing user blows even harder towards the cartoon cake1200 (in FIG. 12). The more intense airflow of the harder blow flowsover the microphone 1107, which is recorded as noise data that is inputinto the detection engine 610. In turn, the detection engine 610 thenoutputs a classification indicating that the user is blowingsufficiently hard (e.g., to trigger final state 950, FIG. 9). Inresponse to the new classification, the response engine 615 updates theaudio response ephemeral message 1102 with an updated cartoon cake 1300in which all the candles are extinguished, and further displays amessage 1305 (“Huzzah!”) congratulating the viewing user for interactingwith the audio response ephemeral message per the instruction 1105and/or instruction 1205.

FIG. 14 is a block diagram illustrating an example software architecture1406, which may be used in conjunction with various hardwarearchitectures herein described. FIG. 14 is a non-limiting example of asoftware architecture, and it will be appreciated that many otherarchitectures may be implemented to facilitate the functionalitydescribed herein. The software architecture 1406 may execute on hardwaresuch as a machine 1400 of FIG. 14 that includes, among other things,processors, memory, and I/O components. A representative hardware layer1452 is illustrated and can represent, for example, the machine 1400 ofFIG. 14. The representative hardware layer 1452 includes a processingunit 1454 having associated executable instructions 1404. The executableinstructions 1404 represent the executable instructions of the softwarearchitecture 1406, including implementation of the methods, components,and so forth described herein. The hardware layer 1452 also includes amemory/storage 1456, which also has the executable instructions 1404.The hardware layer 1452 may also comprise other hardware 1458.

In the example architecture of FIG. 14, the software architecture 1406may be conceptualized as a stack of layers where each layer providesparticular functionality. For example, the software architecture 1406may include layers such as an operating system 1402, libraries 1420,frameworks/middleware 1418, applications 1416, and a presentation layer1414. Operationally, the applications 1416 and/or other componentswithin the layers may invoke API calls 1408 through the software stackand receive a response in the form of messages 1412. The layersillustrated are representative in nature and not all softwarearchitectures have all layers. For example, some mobile orspecial-purpose operating systems may not provide aframeworks/middleware 1418, while others may provide such a layer. Othersoftware architectures may include additional or different layers.

The operating system 1402 may manage hardware resources and providecommon services. The operating system 1402 may include, for example, akernel 1422, services 1424, and drivers 1426. The kernel 1422 may act asan abstraction layer between the hardware and the other software layers.For example, the kernel 1422 may be responsible for memory management,processor management (e.g., scheduling), component management,networking, security settings, and so on. The services 1424 may provideother common services for the other software layers. The drivers 1426are responsible for controlling or interfacing with the underlyinghardware. For instance, the drivers 1426 include display drivers, cameradrivers, Bluetooth® drivers, flash memory drivers, serial communicationdrivers (e.g., Universal Serial Bus (USB) drivers), Wi-Fi® drivers,audio drivers, power management drivers, and so forth depending on thehardware configuration.

The libraries 1420 provide a common infrastructure that is used by theapplications 1416 and/or other components and/or layers. The libraries1420 provide functionality that allows other software components toperform tasks in an easier fashion than by interfacing directly with theunderlying operating system 1402 functionality (e.g., kernel 1422,services 1424, and/or drivers 1426). The libraries 1420 may includesystem libraries 1444 (e.g., C standard library) that may providefunctions such as memory allocation functions, string manipulationfunctions, mathematical functions, and the like. In addition, thelibraries 1420 may include API libraries 1446 such as media libraries(e.g., libraries to support presentation and manipulation of variousmedia formats such as MPEG4, H.264, MP3, AAC, AMR, JPG, or PNG),graphics libraries (e.g., an OpenGL framework that may be used to rendertwo dimensional (2D) and three dimensional (3D) graphic content on adisplay), database libraries (e.g., SQLite that may provide variousrelational database functions), web libraries (e.g., WebKit that mayprovide web browsing functionality), and the like. The libraries 1420may also include a wide variety of other libraries 1448 to provide manyother APIs to the applications 1416 and other softwarecomponents/modules.

The frameworks/middleware 1418 provide a higher-level commoninfrastructure that may be used by the applications 1416 and/or othersoftware components/modules. For example, the frameworks/middleware 1418may provide various graphic user interface (GUI) functions, high-levelresource management, high-level location services, and so forth. Theframeworks/middleware 1418 may provide a broad spectrum of other APIsthat may be utilized by the applications 1416 and/or other softwarecomponents/modules, some of which may be specific to a particularoperating system 1402 or platform.

The applications 1416 include built-in applications 1438 and/orthird-party applications 1440. Examples of representative built-inapplications 1438 may include, but are not limited to, a contactsapplication, a browser application, a book reader application, alocation application, a media application, a messaging application,and/or a game application. The third-party applications 1440 may includean application developed using the ANDROID™ or IOS™ software developmentkit (SDK) by an entity other than the vendor of the particular platform,and may be mobile software running on a mobile operating system such asIOS™, ANDROID™, WINDOWS® Phone, or other mobile operating systems. Thethird-party applications 1440 may invoke the API calls 1408 provided bythe mobile operating system (such as the operating system 1402) tofacilitate functionality described herein.

The applications 1416 may use built-in operating system functions (e.g.,kernel 1422, services 1424, and/or drivers 1426), libraries 1420, andframeworks/middleware 1418 to create user interfaces to interact withusers of the system. Alternatively, or additionally, in some systems,interactions with a user may occur through a presentation layer, such asthe presentation layer 1414. In these systems, the application/component“logic” can be separated from the aspects of the application/componentthat interact with a user.

FIG. 15 is a block diagram illustrating components of a machine 1500,according to some example embodiments, able to read instructions from amachine-readable medium (e.g., a machine-readable storage medium) andperform any one or more of the methodologies discussed herein.Specifically, FIG. 15 shows a diagrammatic representation of the machine1500 in the example form of a computer system, within which instructions1516 (e.g., software, a program, an application, an applet, an app, orother executable code) for causing the machine 1500 to perform any oneor more of the methodologies discussed herein may be executed. As such,the instructions 1516 may be used to implement modules or componentsdescribed herein. The instructions 1516 transform the general,non-programmed machine 1500 into a particular machine 1500 programmed tocarry out the described and illustrated functions in the mannerdescribed. In alternative embodiments, the machine 1500 operates as astandalone device or may be coupled (e.g., networked) to other machines.In a networked deployment, the machine 1500 may operate in the capacityof a server machine or a client machine in a server-client networkenvironment, or as a peer machine in a peer-to-peer (or distributed)network environment. The machine 1500 may comprise, but not be limitedto, a server computer, a client computer, a personal computer (PC), atablet computer, a laptop computer, a netbook, a set-top box (STB), apersonal digital assistant (PDA), an entertainment media system, acellular telephone, a smartphone, a mobile device, a wearable device(e.g., a smart watch), a smart home device (e.g., a smart appliance),other smart devices, a web appliance, a network router, a networkswitch, a network bridge, or any machine capable of executing theinstructions 1516, sequentially or otherwise, that specify actions to betaken by the machine 1500. Further, while only a single machine 1500 isillustrated, the term “machine” shall also be taken to include acollection of machines that individually or jointly execute theinstructions 1516 to perform any one or more of the methodologiesdiscussed herein.

The machine 1500 may include processors 1510, memory/storage 1530, andI/O components 1550, which may be configured to communicate with eachother such as via a bus 1502. The memory/storage 1530 may include amemory 1532, such as a main memory, or other memory storage, and astorage unit 1536, both accessible to the processors 1510 such as viathe bus 1502. The storage unit 1536 and memory 1532 store theinstructions 1516 embodying any one or more of the methodologies orfunctions described herein. The instructions 1516 may also reside,completely or partially, within the memory 1532, within the storage unit1536, within at least one of the processors 1510 (e.g., within theprocessor's cache memory), or any suitable combination thereof, duringexecution thereof by the machine 1500. Accordingly, the memory 1532, thestorage unit 1536, and the memory of the processors 1510 are examples ofmachine-readable media.

The I/O components 1550 may include a wide variety of components toreceive input, provide output, produce output, transmit information,exchange information, capture measurements, and so on. The specific I/Ocomponents 1550 that are included in a particular machine 1500 willdepend on the type of machine. For example, portable machines such asmobile phones will likely include a touch input device or other suchinput mechanisms, while a headless server machine will likely notinclude such a touch input device. It will be appreciated that the I/Ocomponents 1550 may include many other components that are not shown inFIG. 15. The I/O components 1550 are grouped according to functionalitymerely for simplifying the following discussion and the grouping is inno way limiting. In various example embodiments, the I/O components 1550may include output components 1552 and input components 1554. The outputcomponents 1552 may include visual components (e.g., a display such as aplasma display panel (PDP), a light-emitting diode (LED) display, aliquid-crystal display (LCD), a projector, or a cathode ray tube (CRT)),acoustic components (e.g., speakers), haptic components (e.g., avibratory motor, resistance mechanisms), other signal generators, and soforth. The input components 1554 may include alphanumeric inputcomponents (e.g., a keyboard, a touch screen configured to receivealphanumeric input, a photo-optical keyboard, or other alphanumericinput components), point-based input components (e.g., a mouse, atouchpad, a trackball, a joystick, a motion sensor, or other pointinginstruments), tactile input components (e.g., a physical button, a touchscreen that provides location and/or force of touches or touch gestures,or other tactile input components), audio input components (e.g., amicrophone), and the like.

In further example embodiments, the I/O components 1550 may includebiometric components 1556, motion components 1558, environmentcomponents 1560, or position components 1562 among a wide array of othercomponents. For example, the biometric components 1556 may includecomponents to detect expressions (e.g., hand expressions, facialexpressions, vocal expressions, body gestures, or eye tracking), measurebiosignals (e.g., blood pressure, heart rate, body temperature,perspiration, or brain waves), identify a person (e.g., voiceidentification, retinal identification, facial identification,fingerprint identification, or electroencephalogram-basedidentification), and the like. The motion components 1558 may includeacceleration sensor components (e.g., accelerometer), gravitation sensorcomponents, rotation sensor components (e.g., gyroscope), and so forth.The environment components 1560 may include, for example, illuminationsensor components (e.g., photometer), temperature sensor components(e.g., one or more thermometers that detect ambient temperature),humidity sensor components, pressure sensor components (e.g.,barometer), acoustic sensor components (e.g., one or more microphonesthat detect background noise), proximity sensor components (e.g.,infrared sensors that detect nearby objects), gas sensors (e.g., gassensors to detect concentrations of hazardous gases for safety or tomeasure pollutants in the atmosphere), or other components that mayprovide indications, measurements, or signals corresponding to asurrounding physical environment. The position components 1562 mayinclude location sensor components (e.g., a GPS receiver component),altitude sensor components (e.g., altimeters or barometers that detectair pressure from which altitude may be derived), orientation sensorcomponents (e.g., magnetometers), and the like.

Communication may be implemented using a wide variety of technologies.The I/O components 1550 may include communication components 1564operable to couple the machine 1500 to a network 1580 or devices 1570via a coupling 1582 and a coupling 1572, respectively. For example, thecommunication components 1564 may include a network interface componentor other suitable device to interface with the network 1580. In furtherexamples, the communication components 1564 may include wiredcommunication components, wireless communication components, cellularcommunication components, Near Field Communication (NFC) components,Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components,and other communication components to provide communication via othermodalities. The devices 1570 may be another machine or any of a widevariety of peripheral devices (e.g., a peripheral device coupled via aUSB).

Moreover, the communication components 1564 may detect identifiers orinclude components operable to detect identifiers. For example, thecommunication components 1564 may include Radio Frequency Identification(RFID) tag reader components, NFC smart tag detection components,optical reader components (e.g., an optical sensor to detectone-dimensional barcodes such as Universal Product Code (UPC) barcode,multi-dimensional barcodes such as Quick Response (QR) code, Aztec code,Data Matrix, Dataglyph, MaxiCode, PDF415, Ultra Code, UCC RSS-2Dbarcode, and other optical codes), or acoustic detection components(e.g., microphones to identify tagged audio signals). In addition, avariety of information may be derived via the communication components1564, such as location via Internet Protocol (IP) geolocation, locationvia Wi-Fi® signal triangulation, location via detecting an NFC beaconsignal that may indicate a particular location, and so forth.

Glossary

“CARRIER SIGNAL” in this context refers to any intangible medium that iscapable of storing, encoding, or carrying instructions for execution bythe machine, and includes digital or analog communications signals orother intangible media to facilitate communication of such instructions.Instructions may be transmitted or received over the network using atransmission medium via a network interface device and using any one ofa number of well-known transfer protocols.

“CLIENT DEVICE” in this context refers to any machine that interfaces toa communications network to obtain resources from one or more serversystems or other client devices. A client device may be, but is notlimited to, a mobile phone, desktop computer, laptop, PDA, smartphone,tablet, ultrabook, netbook, multi-processor system, microprocessor-basedor programmable consumer electronics system, game console, set-top box,or any other communication device that a user may use to access anetwork.

“COMMUNICATIONS NETWORK” in this context refers to one or more portionsof a network that may be an ad hoc network, an intranet, an extranet, avirtual private network (VPN), a local area network (LAN), a wirelessLAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), ametropolitan area network (MAN), the Internet, a portion of theInternet, a portion of the Public Switched Telephone Network (PSTN), aplain old telephone service (POTS) network, a cellular telephonenetwork, a wireless network, a Wi-Fi® network, another type of network,or a combination of two or more such networks. For example, a network ora portion of a network may include a wireless or cellular network andthe coupling may be a Code Division Multiple Access (CDMA) connection, aGlobal System for Mobile communications (GSM) connection, or anothertype of cellular or wireless coupling. In this example, the coupling mayimplement any of a variety of types of data transfer technology, such asSingle Carrier Radio Transmission Technology (1×RTT), Evolution-DataOptimized (EVDO) technology, General Packet Radio Service (GPRS)technology, Enhanced Data rates for GSM Evolution (EDGE) technology,third Generation Partnership Project (3GPP) including 3G, fourthgeneration wireless (4G) networks, Universal Mobile TelecommunicationsSystem (UMTS), High-Speed Packet Access (HSPA), WorldwideInteroperability for Microwave Access (WiMAX), Long-Term Evolution (LTE)standard, others defined by various standard-setting organizations,other long-range protocols, or other data transfer technology.

“EMPHEMERAL MESSAGE” in this context refers to a message that isaccessible for a time-limited duration. An ephemeral message may be atext, an image, a video, and the like. The access time for the ephemeralmessage may be set by the message sender. Alternatively, the access timemay be a default setting, or a setting specified by the recipient.Regardless of the setting technique, the message is transitory.

“MACHINE-READABLE MEDIUM” in this context refers to a component, adevice, or other tangible media able to store instructions and datatemporarily or permanently and may include, but is not limited to,random-access memory (RAM), read-only memory (ROM), buffer memory, flashmemory, optical media, magnetic media, cache memory, other types ofstorage (e.g., Erasable Programmable Read-Only Memory (EPROM)), and/orany suitable combination thereof. The term “machine-readable medium”should be taken to include a single medium or multiple media (e.g., acentralized or distributed database, or associated caches and servers)able to store instructions. The term “machine-readable medium” shallalso be taken to include any medium, or combination of multiple media,that is capable of storing instructions (e.g., code) for execution by amachine, such that the instructions, when executed by one or moreprocessors of the machine, cause the machine to perform any one or moreof the methodologies described herein. Accordingly, a “machine-readablemedium” refers to a single storage apparatus or device, as well as“cloud-based” storage systems or storage networks that include multiplestorage apparatus or devices. The term “machine-readable medium”excludes signals per se.

“COMPONENT” in this context refers to a device, a physical entity, orlogic having boundaries defined by function or subroutine calls, branchpoints, APIs, or other technologies that provide for the partitioning ormodularization of particular processing or control functions. Componentsmay be combined via their interfaces with other components to carry outa machine process. A component may be a packaged functional hardwareunit designed for use with other components and a part of a program thatusually performs a particular function of related functions. Componentsmay constitute either software components (e.g., code embodied on amachine-readable medium) or hardware components. A “hardware component”is a tangible unit capable of performing certain operations and may beconfigured or arranged in a certain physical manner. In various exampleembodiments, one or more computer systems (e.g., a standalone computersystem, a client computer system, or a server computer system) or one ormore hardware components of a computer system (e.g., a processor or agroup of processors) may be configured by software (e.g., an applicationor application portion) as a hardware component that operates to performcertain operations as described herein. A hardware component may also beimplemented mechanically, electronically, or any suitable combinationthereof. For example, a hardware component may include dedicatedcircuitry or logic that is permanently configured to perform certainoperations. A hardware component may be a special-purpose processor,such as a Field-Programmable Gate Array (FPGA) or anApplication-Specific Integrated Circuit (ASIC). A hardware component mayalso include programmable logic or circuitry that is temporarilyconfigured by software to perform certain operations. For example, ahardware component may include software executed by a general-purposeprocessor or other programmable processor. Once configured by suchsoftware, hardware components become specific machines (or specificcomponents of a machine) uniquely tailored to perform the configuredfunctions and are no longer general-purpose processors. It will beappreciated that the decision to implement a hardware componentmechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations. Accordingly, the phrase“hardware component” (or “hardware-implemented component”) should beunderstood to encompass a tangible entity, be that an entity that isphysically constructed, permanently configured (e.g., hardwired), ortemporarily configured (e.g., programmed) to operate in a certain manneror to perform certain operations described herein.

Considering embodiments in which hardware components are temporarilyconfigured (e.g., programmed), each of the hardware components need notbe configured or instantiated at any one instance in time. For example,where a hardware component comprises a general-purpose processorconfigured by software to become a special-purpose processor, thegeneral-purpose processor may be configured as respectively differentspecial-purpose processors (e.g., comprising different hardwarecomponents) at different times. Software accordingly configures aparticular processor or processors, for example, to constitute aparticular hardware component at one instance of time and to constitutea different hardware component at a different instance of time.

Hardware components can provide information to, and receive informationfrom, other hardware components. Accordingly, the described hardwarecomponents may be regarded as being communicatively coupled. Wheremultiple hardware components exist contemporaneously, communications maybe achieved through signal transmission (e.g., over appropriate circuitsand buses) between or among two or more of the hardware components. Inembodiments in which multiple hardware components are configured orinstantiated at different times, communications between or among suchhardware components may be achieved, for example, through the storageand retrieval of information in memory structures to which the multiplehardware components have access. For example, one hardware component mayperform an operation and store the output of that operation in a memorydevice to which it is communicatively coupled. A further hardwarecomponent may then, at a later time, access the memory device toretrieve and process the stored output. Hardware components may alsoinitiate communications with input or output devices, and can operate ona resource (e.g., a collection of information).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implementedcomponents that operate to perform one or more operations or functionsdescribed herein. As used herein, “processor-implemented component”refers to a hardware component implemented using one or more processors.Similarly, the methods described herein may be at least partiallyprocessor-implemented, with a particular processor or processors beingan example of hardware. For example, at least some of the operations ofa method may be performed by one or more processors orprocessor-implemented components. Moreover, the one or more processorsmay also operate to support performance of the relevant operations in a“cloud computing” environment or as a “software as a service” (SaaS).For example, at least some of the operations may be performed by a groupof computers (as examples of machines including processors), with theseoperations being accessible via a network (e.g., the Internet) and viaone or more appropriate interfaces (e.g., an API). The performance ofcertain of the operations may be distributed among the processors, notonly residing within a single machine, but deployed across a number ofmachines. In some example embodiments, the processors orprocessor-implemented components may be located in a single geographiclocation (e.g., within a home environment, an office environment, or aserver farm). In other example embodiments, the processors orprocessor-implemented components may be distributed across a number ofgeographic locations.

“PROCESSOR” in this context refers to any circuit or virtual circuit (aphysical circuit emulated by logic executing on an actual processor)that manipulates data values according to control signals (e.g.,“commands,” “op codes,” “machine code,” etc.) and which producescorresponding output signals that are applied to operate a machine. Aprocessor may, for example, be a Central Processing Unit (CPU), aReduced Instruction Set Computing (RISC) processor, a ComplexInstruction Set Computing (CISC) processor, a Graphics Processing Unit(GPU), a Digital Signal Processor (DSP), an ASIC, a Radio-FrequencyIntegrated Circuit (RFIC), or any combination thereof. A processor mayfurther be a multi-core processor having two or more independentprocessors (sometimes referred to as “cores”) that may executeinstructions contemporaneously.

“TIMESTAMP” in this context refers to a sequence of characters orencoded information identifying when a certain event occurred (forexample, giving date and time of day, sometimes accurate to a smallfraction of a second).

A portion of the disclosure of this patent document contains materialthat is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the Patent and TrademarkOffice patent files or records, but otherwise reserves all copyrightrights whatsoever.

What is claimed is:
 1. A method comprising: receiving, at a server, afirst message indicating an image and content data associated with anon-verbal audio interaction; generating, at the server, a secondmessage comprising the image, the content data associated with thenon-verbal audio interaction, and an indication to perform thenon-verbal audio interaction; and sending the second message to a userdevice, the user device being configured to: display the image and theindication on a display of the user device, generate sound data from amicrophone of the user device while the message is being displayed onthe user device, determine that the sound data corresponds to thenon-verbal audio interaction, and display the content data on thedisplay in response to determining that the sound data corresponds tothe non-verbal audio interaction.
 2. The method of claim 1, wherein theuser device is configured to: generate a sound classification byapplying a convolutional neural network to the sound data, theconvolutional neural network being trained to detect non-verbal soundsand an intensity level of the non-verbal audio interaction; anddetermine, using the sound classification, that the sound data comprisesthe non-verbal audio interaction.
 3. The method of claim 2, wherein theuser device is configured to: determine, using the convolutional neuralnetwork, that the intensity level of the non-verbal audio interactionsatisfies a pre-configured intensity level, and in response todetermining that the intensity level of the non-verbal audio interactionsatisfies the pre-configured intensity level, enable display of thecontent data.
 4. The method of claim 2, wherein the user device isconfigured to: determine, using the convolutional neural network, thatthe intensity level of the non-verbal audio interaction fails to satisfya pre-configured intensity level, and in response to determining thatthe intensity level of the non-verbal audio interaction fails to satisfythe pre-configured intensity level, prompt the user of the user deviceto increase the intensity level of the non-verbal audio interaction. 5.The method of claim 2, wherein the content data comprises first contentdata, second content data, and third content data.
 6. The method ofclaim 5, wherein the user device is configured to: display the firstcontent data in response to the intensity level of the non-verbal audiointeraction being less than a minimum level threshold and less than amaximum level threshold.
 7. The method of claim 5, wherein the userdevice is configured to: display the second content data in response tothe intensity level of the non-verbal audio interaction being greaterthan a minimum level threshold and less than a maximum level threshold.8. The method of claim 5, wherein the user device is configured to:display the third content data in response to the intensity level of thenon-verbal audio interaction being greater than a minimum levelthreshold and greater than a maximum level threshold.
 9. The method ofclaim 2, wherein the indication prompts a user of the user device toperform the non-verbal audio interaction, wherein the non-verbal audiointeraction detected by the convolutional neural network is at least oneof: blowing air, snapping fingers, clapping hands.
 10. The method ofclaim 1, wherein the non-verbal audio interaction is selected, from aplurality of non-verbal audio interactions, by an author of the firstmessage.
 11. A system comprising: one or more processors of a machine;and a memory storing instructions that, when executed by the one or moreprocessors, cause the machine to perform operations comprising:receiving, at the machine, a first message indicating an image andcontent data associated with a non-verbal audio interaction; generating,at the machine, a second message comprising the image, the content dataassociated with the non-verbal audio interaction, and an indication toperform the non-verbal audio interaction; and sending the second messageto a user device, the user device being configured to: display the imageand the indication on a display of the user device, generate sound datafrom a microphone of the user device while the message is beingdisplayed on the user device, determine that the sound data correspondsto the non-verbal audio interaction, and display the content data on thedisplay in response to determining that the sound data corresponds tothe non-verbal audio interaction.
 12. The system of claim 11, whereinthe user device is configured to: generate a sound classification byapplying a convolutional neural network to the sound data, theconvolutional neural network being trained to detect non-verbal soundsand an intensity level of the non-verbal audio interaction; anddetermine, using the sound classification, that the sound data comprisesthe non-verbal audio interaction.
 13. The system of claim 12, whereinthe user device is configured to: determine, using the convolutionalneural network, that the intensity level of the non-verbal audiointeraction satisfies a pre-configured intensity level, and in responseto determining that the intensity level of the non-verbal audiointeraction satisfies the pre-configured intensity level, enable displayof the content data.
 14. The system of claim 12, wherein the user deviceis configured to: determine, using the convolutional neural network,that the intensity level of the non-verbal audio interaction fails tosatisfy a pre-configured intensity level, and in response to determiningthat the intensity level of the non-verbal audio interaction fails tosatisfy the pre-configured intensity level, prompt the user of the userdevice to increase the intensity level of the non-verbal audiointeraction.
 15. The system of claim 12, wherein the content datacomprises first content data, second content data, and third contentdata.
 16. The system of claim 15, wherein the user device is configuredto: display the first content data in response to the intensity level ofthe non-verbal audio interaction being less than a minimum levelthreshold and less than a maximum level threshold.
 17. The system ofclaim 15, wherein the user device is configured to: display the secondcontent data in response to the intensity level of the non-verbal audiointeraction being greater than a minimum level threshold and less than amaximum level threshold.
 18. The system of claim 15, wherein the userdevice is configured to: display the third content data in response tothe intensity level of the non-verbal audio interaction being greaterthan a minimum level threshold and greater than a maximum levelthreshold.
 19. The system of claim 12, wherein the indication prompts auser of the user device to perform the non-verbal audio interaction,wherein the non-verbal audio interaction detected by the convolutionalneural network is at least one of: blowing air, snapping fingers,clapping hands.
 20. A non-transitory machine-readable storage mediumembodying instructions that, when executed by a machine, cause themachine to perform operations comprising: receiving, at the machine, afirst message indicating an image and content data associated with anon-verbal audio interaction; generating, at the machine, a secondmessage comprising the image, the content data associated with thenon-verbal audio interaction, and an indication to perform thenon-verbal audio interaction; and sending the second message to a userdevice, the user device being configured to: display the image and theindication on a display of the user device, generate sound data from amicrophone of the user device while the message is being displayed onthe user device, determine that the sound data corresponds to thenon-verbal audio interaction, and display the content data on thedisplay in response to determining that the sound data corresponds tothe non-verbal audio interaction.